Commonly images represented by a digital signal such as medical images are subjected to image processing during or prior to displaying or hard copy recording.
The conversion of grey value pixels into values suitable for reproduction or displaying may comprise a multi-scale image processing method (also called multi-resolution image processing method) by means of which the contrast of the image is enhanced.
According to such a multi-scale image processing method an image, represented by an array of pixel values, is processed by applying the following steps. First the original image is decomposed into a sequence of detail images at multiple scales and occasionally a residual image. Next, the pixel values of the detail images are modified by applying to these pixel values at least one conversion function. Finally, a processed image is computed by applying a reconstruction algorithm to the residual image and the modified detail images.
There are limits for the behavior of the conversion functions. Grey value transitions in the image can be distorted to an extent that the appearance becomes unnatural if the conversion functions are excessively non-linear. The distortions are more pronounced in the vicinity of significant grey level transitions, which may result in overshoots at step edges and loss of homogeneity in regions of low variance facing strong step edges. The risk of creating artifacts becomes more significant for CT images since they have sharper grey level transitions, e.g. at the interface of soft tissue and contrast media. One has to be careful using the multi-scale techniques on CT images.
A multi-scale contrast enhancement algorithm which results in a contrast enhanced image while preserving the shape of the edge transitions has been described in co-pending European patent application 06 125 766.3 filed Dec. 11, 2006.
In one embodiment of this method translation difference images of at least one approximation image of the image are created at one or multiple scales. Next, translation difference images are non linearly modified. Then at least one enhanced center difference image at a specific scale is computed by combining modified translation difference images at that scale or at a smaller scale. Spatially-localized phenomena derived from the image can be used to create enhanced center difference images.
Finally an enhanced image is computed by applying a reconstruction algorithm to the enhanced center difference images.
Generally isotropic filters are used in the decomposition and reconstruction process and an omni-directional enhancement is applied to the coefficients in the detail images.
The isotropic design concept is justified in those cases where the image statistics are stationary, meaning that every patch in the image is generated by the same random process as every other patch of the image. However, if one looks at a region of the image where an edge or a line or a homogeneous region might be visible, it is clear that the underlying process is not stationary and changes from patch to patch.
It is an object of the present invention to overcome the limitations of the prior art.
Such a limitation is the inability to facilitate selective detection and enhancement of image features, for example chromosome images wherein one wants to enhance chromosome bands at a particular scale and in certain orientation and position for designated DNA analysis.